Data Platform Engineer (Associate)

Huron helps healthcare organizations drive growth, enhance performance, and sustain leadership by improving operations, clinical outcomes, and consumer experiences. The Associate Data Platform Engineer will unify analytics applications, build scalable integration and data platform services, manage cloud infrastructure, and collaborate with engineering, data, and DevOps teams.

Responsibilities:

• Audit existing analytics applications to understand their underlying technology choices, data flows, and integration points
• Design and implement integration patterns (APIs, event streams, shared data contracts) that allow siloed applications to interoperate without unnecessary rewrites
• Evaluate build vs. consolidate vs. federate tradeoffs for components across the platform, documenting your rationale and driving alignment
• Build and maintain shared platform services — authentication, observability, configuration management, logging — that reduce duplication across applications
• Develop a deep understanding of existing data pipelines owned by distributed teams — including their data sources, transformation logic, and dependencies
• Design and build a unified presentation layer that surfaces data from heterogeneous compute environments — including large-scale distributed systems (e.g., Spark) and traditional relational databases — in a consistent, accessible way
• Partner with domain teams who have the deepest knowledge of their own data — acting as an integration architect and collaborator rather than a centralized pipeline owner; identify unification opportunities but defer to domain expertise on data semantics and processing logic
• Deploy and manage platform services on cloud infrastructure (AWS preferred; Azure/GCP experience a plus)
• Contribute to infrastructure-as-code practices using tools such as Terraform, CDK, or Pulumi
• Collaborate with DevOps/SRE to define deployment pipelines and reliability standards for integration services
• Construct evidence-based business cases for cloud feature adoption — translating technical requirements into business value, risk reduction, and compliance language that resonates with IT governance and procurement stakeholders

Requirements:

• 3+ years of software engineering experience, with at least 1 years focused on integration, platform, or infrastructure work
• Proficiency in at least one backend language commonly used in data-intensive systems (Python, Go, Java, or similar)
• Hands-on experience with cloud platforms (AWS strongly preferred) including compute, storage, networking, and managed services
• Experience building and operating data pipelines (ETL/ELT), including schema management and data quality monitoring
• Working experience with AI-assisted development tooling in a professional engineering context
• Strong written communication skills — able to produce clear architecture decision records (ADRs), runbooks, and design documents
• proficiency in two or more languages strongly preferred
• Experience evaluating and rationalizing heterogeneous technology stacks — i.e., inheriting systems you didn't design and making them work together
• Familiarity with analytics or ML platform tooling (e.g., Airflow, dbt, MLflow, Spark, or SaaS equivalents)
• Experience with API gateway management, service mesh, or distributed tracing tooling
• Background working with both structured (SQL) and semi-structured (JSON, Parquet, Avro) data at scale